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Author: Duncan Cramer
Publisher: McGraw-Hill Education (UK)
ISBN: 0335224660
Category : Social Science
Languages : en
Pages : 268
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Book Description
*What do advanced statistical techniques do? *When is it appropriate to use them? *How are they carried out and reported? There are a variety of statistical techniques used to analyse quantitative data that masters students, advanced undergraduates and researchers in the social sciences are expected to be able to understand and undertake. This book explains these techniques, when it is appropriate to use them, how to carry them out and how to write up the results. Most books which describe these techniques do so at too advanced or technical a level to be readily understood by many students who need to use them. In contrast the following features characterise this book: - concise and accessible introduction to calculating and interpreting advanced statistical techniques - use of a small data set of simple numbers specifically designed to illustrate the nature and manual calculation of the most important statistics in each technique - succinct illustration of writing up the results of these analyses - minimum of mathematical, statistical and technical notation - annotated bibliography and glossary of key concepts Commonly used software is introduced, and instructions are presented for carrying out analyses and interpreting the output using the computer programs of SPSS Release 11 for Windows and a version of LISREL 8.51, which is freely available online. Designed as a textbook for postgraduate and advanced undergraduate courses across the socio-behavioural sciences, this book will also serve as a personal reference for researchers in disciplines such as sociology and psychology.
Author: Duncan Cramer
Publisher: McGraw-Hill Education (UK)
ISBN: 0335224660
Category : Social Science
Languages : en
Pages : 268
Get Book Here
Book Description
*What do advanced statistical techniques do? *When is it appropriate to use them? *How are they carried out and reported? There are a variety of statistical techniques used to analyse quantitative data that masters students, advanced undergraduates and researchers in the social sciences are expected to be able to understand and undertake. This book explains these techniques, when it is appropriate to use them, how to carry them out and how to write up the results. Most books which describe these techniques do so at too advanced or technical a level to be readily understood by many students who need to use them. In contrast the following features characterise this book: - concise and accessible introduction to calculating and interpreting advanced statistical techniques - use of a small data set of simple numbers specifically designed to illustrate the nature and manual calculation of the most important statistics in each technique - succinct illustration of writing up the results of these analyses - minimum of mathematical, statistical and technical notation - annotated bibliography and glossary of key concepts Commonly used software is introduced, and instructions are presented for carrying out analyses and interpreting the output using the computer programs of SPSS Release 11 for Windows and a version of LISREL 8.51, which is freely available online. Designed as a textbook for postgraduate and advanced undergraduate courses across the socio-behavioural sciences, this book will also serve as a personal reference for researchers in disciplines such as sociology and psychology.
Author: Reid Ewing
Publisher: Routledge
ISBN: 1000036421
Category : Architecture
Languages : en
Pages : 307
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Book Description
Advanced Quantitative Research Methods for Urban Planners provides fundamental knowledge and hands-on techniques about research, such as research topics and key journals in the planning field, advice for technical writing, and advanced quantitative methodologies. This book aims to provide the reader with a comprehensive and detailed understanding of advanced quantitative methods and to provide guidance on technical writing. Complex material is presented in the simplest and clearest way possible using real-world planning examples and making the theoretical content of each chapter as tangible as possible. Hands-on techniques for a variety of quantitative research studies are covered to provide graduate students, university faculty, and professional researchers with useful guidance and references. A companion to Basic Quantitative Research Methods for Urban Planners, Advanced Quantitative Research Methods for Urban Planners is an ideal read for researchers who want to branch out methodologically and for practicing planners who need to conduct advanced analyses with planning data.
Author: Reid Ewing
Publisher: Routledge
ISBN: 1000769232
Category : Architecture
Languages : en
Pages : 343
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Book Description
In most planning practice and research, planners work with quantitative data. By summarizing, analyzing, and presenting data, planners create stories and narratives that explain various planning issues. Particularly, in the era of big data and data mining, there is a stronger demand in planning practice and research to increase capacity for data-driven storytelling. Basic Quantitative Research Methods for Urban Planners provides readers with comprehensive knowledge and hands-on techniques for a variety of quantitative research studies, from descriptive statistics to commonly used inferential statistics. It covers statistical methods from chi-square through logistic regression and also quasi-experimental studies. At the same time, the book provides fundamental knowledge about research in general, such as planning data sources and uses, conceptual frameworks, and technical writing. The book presents relatively complex material in the simplest and clearest way possible, and through the use of real world planning examples, makes the theoretical and abstract content of each chapter as tangible as possible. It will be invaluable to students and novice researchers from planning programs, intermediate researchers who want to branch out methodologically, practicing planners who need to conduct basic analyses with planning data, and anyone who consumes the research of others and needs to judge its validity and reliability.
Author: Norman Blaikie
Publisher: SAGE
ISBN: 9780761967590
Category : Social Science
Languages : en
Pages : 380
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Book Description
For social researchers who need to know what procedures to use under what circumstances in practical research projects, this book does not require an indepth understanding of statistical theory.
Author: Christian Geiser
Publisher: Guilford Press
ISBN: 1462502458
Category : Social Science
Languages : en
Pages : 320
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Book Description
A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with real data examples, numerous screen shots, and output excerpts. The author shows how to prepare a data set for import in Mplus using SPSS. He explains how to specify different types of models in Mplus syntax and address typical caveats--for example, assessing measurement invariance in longitudinal SEMs. Coverage includes path and factor analytic models as well as mediational, longitudinal, multilevel, and latent class models. Specific programming tips and solution strategies are presented in boxes in each chapter. The companion website (http://crmda.ku.edu/guilford/geiser) features data sets, annotated syntax files, and output for all of the examples. Of special utility to instructors and students, many of the examples can be run with the free demo version of Mplus.
Author: Raymond A Kent
Publisher: SAGE
ISBN: 1473917913
Category : Social Science
Languages : en
Pages : 425
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Book Description
This innovative book provides a fresh take on quantitative data analysis within the social sciences. It presents variable-based and case-based approaches side-by-side encouraging you to learn a range of approaches and to understand which is the most appropriate for your research. Using two multidisciplinary non-experimental datasets throughout, the book demonstrates that data analysis is really an active dialogue between ideas and evidence. Each dataset is returned to throughout the chapters enabling you to see the role of the researcher in action; it also showcases the difference between each approach and the significance of researchers’ decisions that must be made as you move through your analysis. The book is divided into four clear sections: Data and their presentation Variable-based analyses Case-based analyses Comparing and combining approaches Clear, original and written for students this book should be compulsory reading for anyone looking to conduct non-experimental quantitative data analysis.
Author: Daniel Durstewitz
Publisher: Springer
ISBN: 3319599763
Category : Medical
Languages : en
Pages : 308
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Book Description
This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanatory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most methods are provided through a package of MatLab routines, encouraging a playful approach to the subject, and providing readers with a better feel for the practical aspects of the methods covered. "Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well as mathematically well versed Physicists. The book acts as a window to the issues, to the questions, and to the tools for finding the answers to interesting inquiries about brains and how they function." Henry D. I. Abarbanel Physics and Scripps Institution of Oceanography, University of California, San Diego “This book delivers a clear and thorough introduction to sophisticated analysis approaches useful in computational neuroscience. The models described and the examples provided will help readers develop critical intuitions into what the methods reveal about data. The overall approach of the book reflects the extensive experience Prof. Durstewitz has developed as a leading practitioner of computational neuroscience. “ Bruno B. Averbeck
Author: Yaacov Petscher
Publisher: Routledge
ISBN: 113626633X
Category : Education
Languages : en
Pages : 389
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Book Description
To say that complex data analyses are ubiquitous in the education and social sciences might be an understatement. Funding agencies and peer-review journals alike require that researchers use the most appropriate models and methods for explaining phenomena. Univariate and multivariate data structures often require the application of more rigorous methods than basic correlational or analysis of variance models. Additionally, though a vast set of resources may exist on how to run analysis, difficulties may be encountered when explicit direction is not provided as to how one should run a model and interpret results. The mission of this book is to expose the reader to advanced quantitative methods as it pertains to individual level analysis, multilevel analysis, item-level analysis, and covariance structure analysis. Each chapter is self-contained and follows a common format so that readers can run the analysis and correctly interpret the output for reporting.
Author: Anthony S. Bryk
Publisher: SAGE Publications, Incorporated
ISBN:
Category : Mathematics
Languages : en
Pages : 294
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Book Description
Hierarchical Linear Models launches a new Sage series, Advanced Quantitative Techniques in the Social Sciences. This introductory text explicates the theory and use of hierarchical linear models (HLM) through rich, illustrative examples and lucid explanations. The presentation remains reasonably nontechnical by focusing on three general research purposes - improved estimation of effects within an individual unit, estimating and testing hypotheses about cross-level effects, and partitioning of variance and covariance components among levels. This innovative volume describes use of both two and three level models in organizational research, studies of individual development and meta-analysis applications, and concludes with a formal derivation of the statistical methods used in the book.
Author: Judith Bell
Publisher: McGraw-Hill Education (UK)
ISBN: 0335243398
Category : Education
Languages : en
Pages : 363
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Book Description
*Interested in purchasing Doing Your Research Project as a SmartBook? Visit https://connect2.mheducation.com/join/?c=bellwaters7e to register for access today* Step-by-step advice on completing an outstanding research project. This is the market-leading book for anyone conducting a research project, whether for the first time or as an experienced researcher honing their skills. Clear, concise and readable, this bestselling resource provides a practical, step-by-step guide from initial concept to completion of your research report. Thoroughly updated but retaining its well-loved style, this seventh edition provides: • A brand new first chapter outlining what it means to carry out research, the responsibilities of the researcher, the research journey, and the 'intentional' and 'unintentional' roles of a researcher. • An extensive update to chapter nine on using social media in research, to include ethical considerations and how the researcher can use and reference information collected via these platforms and create collaborative connections. • An online review of the latest tools for collecting and analysing both quantitative and qualitative data gathered from social media sites, such as Survey Monkey and Google Forms. • Further coverage on how to protect research participants, including advice from the NHS on how to conduct research in health-based settings. • More detailed coverage of how to conduct effective online literature searches, not only using Google but also other research-based search engines such as PubMed and professionally-focussed sites. • To support your learning, questions at the end of each chapter, which prompt you to reflect on your research journey. This practical, no-nonsense guide is vital reading for all those embarking on undergraduate or postgraduate study, irrespective of discipline, and for professionals in such fields as social science, education and health. 'The latest edition provides extensive coverage of all that a research student might need to know. The expanse of the topics covered enables this book to be indispensable to a great range of students, not only at different levels of study but also in a variety of disciplines. Bell and Waters present an honest and practical look at a daunting academic undertaking and provide the student with a resource that is currently has no parallel. This new edition brings the text up to date with a look at some of the more creative approaches the research project might take and challenges students to think before making research decisions.' Dr Susan Schutz PhD, MSc, RNT, RGN, Department of Nursing, Faculty of Health and Life Sciences, Oxford Brookes University, UK
